Floor shape optimization for green building design

Wang, Weimin; Rivard, Hugues; Zmeureanu, Radu

doi:10.1016/j.aei.2006.07.001

Cited by 216 publications

(108 citation statements)

References 14 publications

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“…The GA generates inputs to the building simulation software, while the later return simulation results on energy consumption, cost and return the values back to GA for optimization. Selection of the inputs are based on the findings from open literature (Wang et al, 2006;Dubrow and Krarti, 2010;Hamdy et al, 2011;Zhang et al, 2011;Gong et al, 2012;Jin and Jeong, 2014;Ascione et al, 2015;Liu et al, 2015;Yu et al, 2015). The design parameters selected in this paper are related to building orientation, WWR, window shading, heating temperature set point, cooling temperature set point, external wall structure (insulation), roof structure (insulation), and glazing type.…”

Section: Methodology Optimization Frameworkmentioning

confidence: 99%

“…Therefore, the best building orientation recommended by the design standard JGJ134-2010 (JGJ, 2010) is adopted, and the building shape is a rectangle, as recommend by Dubrow and Krarti (2010) and Wang et al (2006). In this research, a 10 m × 10 m single-story concrete frame residential building, with height of 4 m with ceiling (see Figure 4), is selected for case study.…”

Section: Reference Building Modelmentioning

confidence: 99%

“…Dubrow and Krarti (2010) combined GA with DOE-2 to optimize building shape and types of building envelopes to minimize the life cycle cost (LCC) and found that the LCC for rectangular and trapezoidal shape buildings have the best performance as compared to L shape, H shape, U shape, and T shape. Wang et al (2006) applied MOGA to find the optimum trade-offs between LCC and life cycle environmental impact (LCEI), where building shape, wall type, roof type, and floor type, window type and WWR are considered. It was found that the rectangular shape performed better than the "L" shape in Montreal.…”

Section: Introductionmentioning

confidence: 99%

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Application of Multi-Objective Genetic Algorithm Based Simulation for Cost-Effective Building Energy Efficiency Design and Thermal Comfort Improvement

Lin

Wang

2018

Front. Energy Res.

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Building design following the energy efficiency standards may not achieve the optimal performance in terms of investment cost, energy consumption and thermal comfort. In this paper, an improved multi-objective genetic algorithm (NSGA-II) is combined with building simulation to assist building design optimization for five selected cities located in the hot summer and cold winter region in China. The trade-offs between the annual energy consumption (AEC) and initial construction cost, as well as between life cycle cost (LCC) and number of thermal discomfort hours, were explored. Sensitivity analysis of various design parameters on building energy consumption is performed. The optimizations predicted AEC reduction of 29.08% on average, as compared to a reference building designed following the standard, and 38.6% with 3.18% more cost on the initial investment. New values for a number of building design parameters are recommended for the revision of relevant building energy efficiency standard.

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Section: Methodology Optimization Frameworkmentioning

confidence: 99%

Section: Reference Building Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Multi-Objective Genetic Algorithm Based Simulation for Cost-Effective Building Energy Efficiency Design and Thermal Comfort Improvement

Lin

Wang

2018

Front. Energy Res.

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“…The GAs consider many points in the search space simultaneously, not a single point, thus they have a reduced chance of converging to local minimum, in which other algorithms may end up [107]. The GAs with the Pareto concept are used widely in energy and buildings studies [7,16,40,41,47,48,92,94,102,110,134,135,136]. According to the studies of Zitzler [137] and Deb [128], the elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) seems to be the most efficient GAs.…”

Section: Bpo Objectives (Single-objective and Multi-objective Functions)mentioning

confidence: 99%

Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design

Attia

Hamdy

O’Brien³

et al. 2013

Energy and Buildings

359

192

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This paper summarizes a study undertaken to reveal potential challenges and opportunities for integrating optimisation tools in Net Zero Energy Buildings (NZEB) Design. The paper reviews current trends in simulationbased Building Performance Optimisation (BPO) and outlines major criteria for optimisation tools selection and evaluation. This is based on analyzing user's needs for tools capabilities and requirement specifications. The review is carried out by means of a literature review of 165 publications and interviews with 28 optimisation experts. The findings are based on an inter-group comparison between experts. The aim is to assess the gaps and needs for integrating BPO tools in NZEB Design. The findings indicate existing limitations including model uncertainty, computation time, difficulty of use and steep learning curve. Some future directions anticipated or needed for improvement of current tools are presented.

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“…The concept of a "green building" is particularly relevant to these efforts by fully harnessing the available natural resources to reduce pollution, and achieve the aim to create the best environment with the least resources. As Wang [1] mentioned, shape is an important consideration in green building design due to its significant impact on energy performance and construction costs. Therefore, building design must take many different factors into account in order to meet the requirements of a green building.…”

Section: Introductionmentioning

confidence: 99%

Visual Req Calculation Tool for Green Building Evaluation in Taiwan

Chang¹,

Lee²,

Chen³

et al. 2011

28th International Symposium on Automation and Robotics in Construction (ISARC 2011)

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ABSTRACT：The concept of a "green building" was first introduced to Taiwan in 1999, and began to develop regulations for the design and evaluation of energy-saving buildings. The Ratio of Equivalent Transparency (Req) is a basic index for assessing whether a building is energy-efficient. Req is the ratio of the area of total building envelope and the area of envelope equivalent transparency. Calculation of Req requires not simply the consideration of natural factors such as building location, direction, ambient lighting and sunshine, but also and physical factors such as material, structure, ventilation and sunshade. Furthermore, Req is considered particularly applicable due to the ubiquity of terraced houses in Taiwan, given the country's high population density. In this study, the correction factor to include the effect of party walls is added into the formula of Req calculation to prevent distortions to the area calculation of the building envelope. Current practices in Taiwan of manually calculating Req render the results prone to error, and are also time-consuming. To address these issues, this research developed a visual Req calculation tool based on a 3D environment. This system provides users with various visualization tools to view the status and Req results of the building project. Furthermore, object-oriented modeling and parametric design can shorten the time taken to look-up tables and simplify the process of Req calculation, and also help to reduce computation time and errors.

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Floor shape optimization for green building design

Cited by 216 publications

References 14 publications

Application of Multi-Objective Genetic Algorithm Based Simulation for Cost-Effective Building Energy Efficiency Design and Thermal Comfort Improvement

Application of Multi-Objective Genetic Algorithm Based Simulation for Cost-Effective Building Energy Efficiency Design and Thermal Comfort Improvement

Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design

Visual Req Calculation Tool for Green Building Evaluation in Taiwan

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